We describe SLING, a framework for parsing natural language into semantic frames.
SLING supports general transition-based, neural-network parsing with bidirectional
LSTM input encoding and a Transition Based Recurrent Unit (TBRU) for output
decoding. The parsing model is trained end-to-end using only the text tokens as
input. The transition system has been designed to output frame graphs directly
without any intervening symbolic representation. The SLING framework includes an
efficient and scalable frame store implementation as well as a neural network JIT
compiler for fast inference during parsing. SLING is implemented in C++ and it is
available for download on GitHub.